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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

On governing equations for crack layer propagation

Results of analysis on damage distribution of a crack layer, in a model material, supported the self-similarity hypothesis of damage evolution which has been adopted by the crack layer theory. On the basis of measurements of discontinuity density and the double layer potential technique, a solution to the crack damage interaction problem has been developed. Evaluation of the stress intensity factor illustrated the methodology. Analysis of experimental results showed that Arrhenius type constitutive relationship described very well the expansion of the active zone of a crack layer.

Chudnovsky, A.↗
NASA NTRS2003

Main Chamber Injectors for Advanced Hydrocarbon Booster Engines

Achieving the highest possible specific impulse has long been a key driver for space launch systems. Recently, more importance has been placed on the need for increased reliability and streamlined launch operations. These general factors along with more specific mission requirements have provided a new focus that is centered on the oxidizer rich staged combustion (ORSC) cycle. Despite a history of use in Russia that extends back to the 1960's, a proven design methodology for ORSC cycle engines does not exist in the West. This lack of design expertise extends to the main chamber injector, a critical subcomponent that largely determines the engine performance and main chamber life. The goals of the effort described here are to establish an empirical knowledge base to provide a fundamental understanding of main chamber injectors and for verification of an injector design methodology for the ORSC cycle. The design of a baseline injector element, derived from information on Russian engines in the open literature, is presented. The baseline injector comprises a gaseous oxidizer core flow and an annular swirling fuel flow. Sets of equations describing the steady-state and the dynamic characteristics of the injector are presented; these equations, which form the basis of the design analysis methodology, will be verified in tests later this year. On-going cold flow studies, using nitrogen and water as simulants, are described which indicate highly atomized and symmetric sprays.

Long, Matthew R.↗
DOE OSTI2022

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Resolution of a Reflector Shroud Fatigue Failure

Two cracks were observed on a reflector shroud for a space program after previously being subjected to the protoflight test campaign and several regression tests. After extensive analysis and investigations, the failure mechanism was identified to be fatigue as a result of the numerous vibration tests imposed on the unit. Two feasible corrective actions were proposed: first, a notched vibration profile which possesses sufficient margin from the anticipated acoustic and launch loads, while maintaining adequate fatigue life through launch and on-orbit operations, and second, a re-design of the shroud to strengthen the fatigue-susceptible areas. In this paper, we present the inspections, testing, and analysis performed to establish that the cracks were a result of fatigue failure. We discuss the conservative fatigue analysis methodology used in the development of both corrective action options. Finally, we review the lessons learned and the actions incorporated into the rework, subsequent regression testing, and the test plans to minimize the risk of recurrence in future units.

response limiting↗
NASA NTRS1988

NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)/EXPERT: Bridging the gap between artificial intelligence and FORTRAN

The development of a probabilistic structural analysis methodology (PSAM) is described. In the near-term, the methodology will be applied to designing critical components of the next generation space shuttle main engine. In the long-term, PSAM will be applied very broadly, providing designers with a new technology for more effective design of structures whose character and performance are significantly affected by random variables. The software under development to implement the ideas developed in PSAM resembles, in many ways, conventional deterministic structural analysis code. However, several additional capabilities regarding the probabilistic analysis makes the input data requirements and the resulting output even more complex. As a result, an intelligent front- and back-end to the code is being developed to assist the design engineer in providing the input data in a correct and appropriate manner. The type of knowledge that this entails is, in general, heuristically-based, allowing the fairly well-understood technology of production rules to apply with little difficulty. However, the PSAM code, called NESSUS, is written in FORTRAN-77 and runs on a DEC VAX. Thus, the associated expert system, called NESSUS/EXPERT, must run on a DEC VAX as well, and integrate effectively and efficiently with the existing FORTRAN code. This paper discusses the process undergone to select a suitable tool, identify an appropriate division between the functions that should be performed in FORTRAN and those that should be performed by production rules, and how integration of the conventional and AI technologies was achieved.

Fink, Pamela K.↗
NASA NTRS2004

Enhanced Characterization of Microorganisms in the Spacecraft Environment

Spacecraft such as the International Space Station (ISS) and the space shuttles are enclosed environments where crewmembers may spend long periods of time. Currently, crewmembers spend approximately a period of 6 months in the ISS. It is known that these prolonged stays in space may result in weakening of the immune system. Therefore, exposure to opportunistic pathogens or high concentrations of environmental microorganisms may compromise the health of the crew. The detection of biocontaminants in spacecraft environments utilizes culture-based methodology, omitting greater than 90% of all microorganisms including pathogens such as Legionella and Cryptosporidium. Culturable bacteria and fungi have been the only allergens studied; the more potent allergens, such as those from dust mites, have never been tested for in spacecraft environments. In addition, no attempts have been made to monitor microbial toxins in spacecrafts. The present study utilized quantitative polymerase chain reaction (QPCR) as a novel approach for monitoring microorganisms in the spacecraft environment. QPCR is a molecular biology technique that does not rely on the physiological state of the organisms for identification, thereby enabling detection of both culturable and non-culturable organisms. In this project, specific molecular primers and probes were utilized for the detection and quantitation of two fungi of concern in indoor environments, Aspergillus fumigatus and Stachybotrys chartarum. These organisms were selected because of the availability of PCR primers and probes, and to establish the sample processing and analysis methodology that may be employed with additional organisms. Purification methods and QPCR assays were optimized for the detection of these organisms in air, surface, and water; and sample processing and analysis protocols were developed. Preliminary validation of these protocols was conducted in the laboratory with air, surface, and water samples seeded with known concentrations of the target organisms. Additional studies were conducted with bulk materials (HEPA filter pleats and particulate found on the filter screen) obtained from the ISS.

Cruz, Patricia↗
NASA NTRS2007

Computational Fluid Dynamics-Based Aeroservoelastic Analysis with Hyper-X Applications

A finite element computational fluids dynamics-based aeroservoelastic analysis methodology is presented in this paper, in which both structural and fluids discretization are achieved by the finite element method, and their interaction is modeled by the transpiration boundary condition technique. In the fluids discipline either inviscid or viscous flow may be accounted for, usually employing unstructured grids.Adescription of a novel viscous flow solver employing unstructured grids is given in detail. Provisions are made for digital as well as analog controllers. These new aeroservoelastic analysis techniques are next applied for the solution of a number of example problems including the novel Hyper-X launch vehicle. Experimental and actual flight test data are also compared with analysis results that signify to the efficacy and accuracy of the newly developed solution procedures.

Gupta, K. K.↗
DOE OSTI2020

LA17-V-InverseRadTransportProblem-PD2Kb. Final Project Report

In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2003

Modeling, Analyzing, and Mitigating Dissonance Between Alerting Systems

Alerting systems are becoming pervasive in process operations, which may result in the potential for dissonance or conflict in information from different alerting systems that suggests different threat levels and/or actions to resolve hazards. Little is currently available to help in predicting or solving the dissonance problem. This thesis presents a methodology to model and analyze dissonance between alerting systems, providing both a theoretical foundation for understanding dissonance and a practical basis from which specific problems can be addressed. A state-space representation of multiple alerting system operation is generalized that can be tailored across a variety of applications. Based on the representation, two major causes of dissonance are identified: logic differences and sensor error. Additionally, several possible types of dissonance are identified. A mathematical analysis method is developed to identify the conditions for dissonance originating from logic differences. A probabilistic analysis methodology is developed to estimate the probability of dissonance originating from sensor error, and to compare the relative contribution to dissonance of sensor error against the contribution from logic differences. A hybrid model, which describes the dynamic behavior of the process with multiple alerting systems, is developed to identify dangerous dissonance space, from which the process can lead to disaster. Methodologies to avoid or mitigate dissonance are outlined. Two examples are used to demonstrate the application of the methodology. First, a conceptual In-Trail Spacing example is presented. The methodology is applied to identify the conditions for possible dissonance, to identify relative contribution of logic difference and sensor error, and to identify dangerous dissonance space. Several proposed mitigation methods are demonstrated in this example. In the second example, the methodology is applied to address the dissonance problem between two air traffic alert and avoidance systems: the existing Traffic Alert and Collision Avoidance System (TCAS) vs. the proposed Airborne Conflict Management system (ACM). Conditions on ACM resolution maneuvers are identified to avoid dynamic dissonance between TCAS and ACM. Also included in this report is an Appendix written by Lee Winder about recent and continuing work on alerting systems design. The application of Markov Decision Process (MDP) theory to complex alerting problems is discussed and illustrated with an abstract example system.

Song, Lixia↗
NASA NTRS1995

Numerical Analysis of Intra-Cavity and Power-Stream Flow Interaction in Multiple Gas-Turbine Disk-Cavities

A numerical analysis methodology and solutions of the interaction between the power stream and multiply-connected multi-cavity sealed secondary flow fields are presented. Flow solutions for a multi-cavity experimental rig were computed and compared with experimental data of Daniels and Johnson. The flow solutions illustrate the complex coupling between the main-path and the cavity flows as well as outline the flow thread that exists throughout the subplatform multiple cavities and seals. The analysis also shows that the de-coupled solutions on single cavities is inadequate. The present results show trends similar to the T-700 engine data that suggests the changes in the CDP seal altered the flow fields throughout the engine and affected the engine performance.

Athavale, M. M.↗
NASA NTRS1998

A Progressive Damage Methodology for Residual Strength Predictions of Notched Composite Panels

The translaminate fracture behavior of carbon/epoxy structural laminates with through-penetration notches was investigated to develop a residual strength prediction methodology for composite structures. An experimental characterization of several composite materials systems revealed a fracture resistance behavior that was very similar to the R-curve behavior exhibited by ductile metals. Fractographic examinations led to the postulate that the damage growth resistance was primarily due to fractured fibers in the principal load-carrying plies being bridged by intact fibers of the adjacent plies. The load transfer associated with this bridging mechanism suggests that a progressive damage analysis methodology will be appropriate for predicting the residual strength of laminates with through-penetration notches. A progressive damage methodology developed by the authors was used to predict the initiation and growth of matrix cracks and fiber fracture. Most of the residual strength predictions for different panel widths, notch lengths, and material systems were within about 10% of the experimental failure loads.

Coats, Timothy W.↗
NASA NTRS2013

Measuring Temperature-Dependent Propagating Disturbances in Coronal Fan Loops Using Multiple SDO-AIA Channels and Surfing Transform Technique

A set of co-aligned high resolution images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) is used to investigate propagating disturbances (PDs) in warm fan loops at the periphery of a non-flaring active region NOAA AR 11082. To measure PD speeds at multiple coronal temperatures, a new data analysis methodology is proposed enabling quantitative description of sub visual coronal motions with low signal-to-noise ratios of the order of 0.1. The technique operates with a set of one-dimensional surfing signals extracted from position-timeplots of several AIA channels through a modified version of Radon transform. The signals are used to evaluate a two-dimensional power spectral density distribution in the frequency - velocity space which exhibits a resonance in the presence of quasi-periodic PDs. By applying this analysis to the same fan loop structures observed in several AIA channels, we found that the traveling velocity of PDs increases with the temperature of the coronal plasma following the square root dependence predicted for the slow mode magneto-acoustic wave which seems to be the dominating wave mode in the studied loop structures. This result extends recent observations by Kiddie et al. (2012) to a more general class of fan loop systems not associated with sunspots and demonstrating consistent slow mode activity in up to four AIA channels.

Solar Corona↗
NASA NTRS1992

Semi-coupled flow and thermal analysis of the field joint during rapid pressurization of the redesigned solid rocket motor

A transient, semi-coupled, multi-dimensional thermal and flow analysis methodology was developed to predict the thermal/gas dynamic conditions in the field joint region of the Redesigned Solid Rocket Motor (RSRM). Transient temperature response, pressure history, and combustion gas flow rate (within the field joint region), were of principle interest, in the course of this study. The thermal environment in the field joint was modeled using SINDA, a finite difference based thermal network analyzer. The combustion gas flow boundary condition was generated using the FLAP code; this code performs a transient, lumped-parameter, control volume analysis to solve the mass, momentum, and energy conservation equations. The FLAP computer code was modified to account for erosion of the NBR insulation material, following ignition. An independent grid sensitivity study was conducted to determine an appropriate grid distribution near the wall. The predicted results, obtained using an optimum grid distribution and computer generated flow boundary condition, were compared with subscale test data.

Ghaffarian, Benny↗
NASA NTRS2012

Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

Improvements to global and regional numerical weather prediction (NWP) have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) that mimics the analysis methodology, domain, and observational datasets for the regional North American Mesoscale (NAM) model run at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) are run to examine the impact of each type of AIRS data set. The first configuration will assimilate the AIRS radiance data along with other conventional and satellite data using techniques implemented within the operational system; the second configuration will assimilate AIRS retrieved profiles instead of AIRS radiances in the same manner. Preliminary results of this study will be presented and focus on the analysis impact of the radiances and profiles for selected cases.

Zavodsky, Bradley↗
NASA NTRS2011

Common Bolted Joint Analysis Tool

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

Imtiaz, Kauser↗
DOE OSTI2021

Analysis and Optimization of a Novel Hexagonal Waveguide Concentrator for Solar Thermal Applications

This paper analyzes a novel, cost-effective planar waveguide solar concentrator design that is inspired by cellular hexagonal structures in nature with the benefits of facile installation and low operation and maintenance cost. A coupled thermal and optical analysis of solar irradiation through an ideal hexagonal waveguide concentrator integrated with a linear receiver is presented, along with a cost analysis methodology, to establish the upper limit of performance. The techno-economic model, coupled with numerical optimization, is used to determine designs that maximized power density and minimized the cost of heat in the temperature range of 100–250 °C, which constitutes more than half of the industrial process heat demand. Depending on the incident solar irradiation and the application temperature, the cost of heat for the optimal design configuration ranged between 0.1–0.27 $/W and 0.075–0.18 $/W for waveguide made of ZK7 glass and polycarbonate, respectively. A techno-economic analysis showed the potential of the technology to achieve cost as low as 80 $/m2 and 61 $/m2 for waveguide made of ZK7 glass and polycarbonate material, respectively, which is less than half the cost of state-of-the-art parabolic trough concentrators. Overall, the hexagonal waveguide solar concentrator technology shows immense potential for decarbonizing the industrial process heat and thermal desalination sectors.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗
DOE OSTI2023

SOLAr Critical Infrastructure Energization (SOLACE): Leveraging Distributed Energy Resources to Provide Local Power

This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.

14 SOLAR ENERGY↗